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Genome analysis and annotation Genome analysis and annotation Part II Part II

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Genome analysis and annotationGenome analysis and annotationPart IIPart II

THE INSTITUTE FOR GENOMIC RESEARCHTHE INSTITUTE FOR GENOMIC RESEARCHTIGRTIGRTIGRTIGR

Evidence ViewEvidence ViewS.mansoni PASA assemblies

S. japonicum EST alignments

Genewise alignments(predictions)

nr Protein Alignments

Caenorhabditis sp. Protein Alignments

Brugia malayi Protein Alignments

Modeling a geneModeling a gene

Sequence Database HitsTop: Protein matchesBottom: EST matches

GenePredictions

Annotated GeneTop: editing panel

Bottom: final curation

Splice site predictions:red: acceptor sitesblue: donor sites

Not shown graphically: gene name, nucleotide and protein sequence, MW, pI, organellar targeting sequence, membrane spanning regions, other domains.

Screenshot of a component within Neomorphic’s annotation station: www.neomorphic.com

Attributes of individual annotated genesAttributes of individual annotated genes

Assigning function to predicted gene productsAssigning function to predicted gene products

E.coli

H. influenzae

M. genitalium

E.coli

H. influenzae

H. influenzae

M. genitalium

H. influenzae

Assigning function to predicted gene productsAssigning function to predicted gene products

The primary tool for assigning function is homology to well characterized proteins

…however transitive annotation can lead to errors that propagate.

The modular nature of proteins can provide the basis for functional annotation

• Proteins may share features that give clues to their structure and/or function

• A domain is a region of a protein that can adopt a particular three-dimensional structure. Together a group of proteins that share a domain is called a family. There are several databases of protein families such as Pfam (http://www.sanger.ac.uk/Software/Pfam/)

• Motifs are short, conserved regions of proteins, typically consisting of a pattern of amino acids that characterizes a prrotein family (http://www.expasy.org/prosite/) EF-hand: D-[DNS]-{ILVFYW}-[DENSTG]-[DNQGHRK]-{GP}-[LIVMC]-[DENQSTAGC]-x(2)- [DE]-[LIVMFYW]

3) HMM domains can also be defined and used to group proteins into families

Top 20 PFAM domains in A. fumigatusCounts in A. nidulans and A. oryzae

PF00400 WD domain, G-beta repeat 532 598 541

PF00023 Ankyrin repeat 368 633 430

PF00083 major facilitator superfamily protein 166 281 219

PF00172 Fungal Zn(2)-Cys(6) binuclear cluster domain 146 179 211

PF00515 TPR Domain 139 142 152

PF00096 Zinc finger, C2H2 type 124 113 142

PF04082 Fungal specific transcription factor domain 110 163 159

PF00153 Mitochondrial carrier protein 106 114 100

PF00069 Protein kinase domain 105 105 101

PF00005 ABC transporter 93 129 86

PF00076 RNA recognition motif. (a.k.a. RRM, RBD, or RNP domain) 93 93 99

PF00106 oxidoreductase, short chain dehydrogenase/reductase family 92 135 129

PF00271 Helicase conserved C-terminal domain 73 80 69

PF00067 Cytochrome P450 63 134 102

PF00107 oxidoreductase, zinc-binding dehydrogenase family 61 107 80

PF00501 AMP-binding enzyme 61 77 83

PF00560 Leucine Rich Repeat 47 50 54

PF00550 Phosphopantetheine attachment site 46 54 60

PF00036 EF hand 10 52 50

Afu Ana Aoa

Protein domain frequencies can yield insights into the biology of an organism

Domain based Paralogous Families can be genrated

Domain Content of Entire Proteome can be computed

All the proteins from a genome

HMM search against Pfam profiles Alignment search against homology-based domain alignments

The search results are stored in the database in the form of domain-based alignments

Organize the proteins into domain-based paralogous families

•Related families share one or more domains with other families•Many putative novel domains are extensions of existing domains

ACA---ATGTCAACTATCACAC--AGCAGA---ATCACCG--ATC

Hidden Markov Models (HMMs)Hidden Markov Models (HMMs)

Seed:

Model:

Statistical representations of sequence patterns.

A query sequence is scored by how likely is it that the HMM would produce it.

Procedure for Preparing a HMM SeedProcedure for Preparing a HMM Seed

Inspect and edit a pairwise aligned group of gene products:Inspect and edit a pairwise aligned group of gene products:

- Eliminate fragments- Eliminate fragments

- Correct the alignment- Correct the alignment

- Remove sequence outside domain- Remove sequence outside domain

- Eliminate redundancy - Eliminate redundancy

- BLAST, annotate and possibly expand the seed.- BLAST, annotate and possibly expand the seed.

THE INSTITUTE FOR GENOMIC RESEARCHTHE INSTITUTE FOR GENOMIC RESEARCHTIGRTIGRTIGRTIGR

Homology-Based Alignment:

HMM Seed:

Trusted Hits:

What is Gene Ontology (GO)?What is Gene Ontology (GO)?

The Gene Ontology is a set of dynamic controlled vocabularies used to The Gene Ontology is a set of dynamic controlled vocabularies used to describe gene products in terms of their associated biological processes, describe gene products in terms of their associated biological processes, cellular components and molecular functions in a species-independent cellular components and molecular functions in a species-independent manner (www.geneontology.org)manner (www.geneontology.org)

The Three OntologiesThe Three Ontologies

Molecular function, biological process and cellular Molecular function, biological process and cellular component are considered attributes of gene products. component are considered attributes of gene products.

Biological Process (a)Biological Process (a)A biological objectiveA biological objectivehas more than one distinct stephas more than one distinct step

Molecular Function (b)Molecular Function (b)what the gene product does what the gene product does Think ‘activity’Think ‘activity’

Cellular Component (c)Cellular Component (c)location in the cell (or smaller unit)location in the cell (or smaller unit)or part of a complexor part of a complex

Assigning GO IDsAssigning GO IDs

Each GO ID is qualified with an evidence code.

Evidence codes are:IMP – inferred from mutant phenotypeIGI—inferred from genetic interactionIPI—inferred from physical interactionIDA—inferred from direct assayIEP—inferred from expression patternISS—inferred from structural similarityIEA—inferred from electronic annotationIC—inferred by curatorTAS—traceable author statementNAS—non-traceable author statementND—no biological data available NR—no longer used

•Experimental evidence•Sequence similarity•Calculated by algorithm•Author statement

The “with/to” fieldISS, IPI, IGI require the accession of the similarity hit, the interacting entity

Gene ontologies can help interpret large scale datasetsGene ontologies can help interpret large scale datasets

K-means clustering using TIGR Multi-Experiment Viewer (TMEV)K-means clustering using TIGR Multi-Experiment Viewer (TMEV)

Cluster 4Cluster 4

Cluster 10Cluster 10

methanogenesis

methanogenesis

Translation, transcription

Translation, transcription